2026-09-18T19:12:01Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/448582022-01-13T07:54:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Leon Glicksman.
Ricker, Elizabeth, S.M. (Elizabeth Ann). Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2009-03-16T19:52:06Z
2009-03-16T19:52:06Z
2008
2008
http://hdl.handle.net/1721.1/44858
301745198
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.
Includes bibliographical references (p. 326-338).
This work investigates methods for predicting retrofit energy savings in existing Norwegian buildings. A case study is performed on a 30 year old primary school in Trondheim, Norway. The energy consumption in the school is simulated with the EnergyPlus computer software and calibrated against measured utility data. Two simulation calibration techniques are investigated: manual calibration and Latin Hypercube Monte Carlo (LHMC) analysis. LHMC is a statistical technique for calibrating building energy simulations, whereas manual calibrations are tuned by the modeler. Calibrated simulations are then used to predict the potential for energy savings under a number of retrofit conditions. Methods of quantifying the uncertainty in energy savings predictions are also investigated. The LHMC is shown to be most appropriate for models with a high number of uncertain building simulation inputs and when monthly utility data is available. However, manual calibration is found to be more suitable for simulations with fewer uncertain inputs and when hourly utility data is available. The retrofit analysis with the manually calibrated model predicted savings of up to 55% of the 173 kWh/m² base-year energy consumption in the case study building.
by Elizabeth Ricker.
S.M.
338 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Assessing methods for predicting retrofit energy savings in buildings : case study of a Norwegian school
Thesis
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<Abstract>This work investigates methods for predicting retrofit energy savings in existing Norwegian buildings. A case study is performed on a 30 year old primary school in Trondheim, Norway. The energy consumption in the school is simulated with the EnergyPlus computer software and calibrated against measured utility data. Two simulation calibration techniques are investigated: manual calibration and Latin Hypercube Monte Carlo (LHMC) analysis. LHMC is a statistical technique for calibrating building energy simulations, whereas manual calibrations are tuned by the modeler. Calibrated simulations are then used to predict the potential for energy savings under a number of retrofit conditions. Methods of quantifying the uncertainty in energy savings predictions are also investigated. The LHMC is shown to be most appropriate for models with a high number of uncertain building simulation inputs and when monthly utility data is available. However, manual calibration is found to be more suitable for simulations with fewer uncertain inputs and when hourly utility data is available. The retrofit analysis with the manually calibrated model predicted savings of up to 55% of the 173 kWh/m² base-year energy consumption in the case study building.</Abstract>
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